100+ datasets found
  1. Inform E-learning GIS Course

    • americansamoa-data.sprep.org
    • samoa-data.sprep.org
    • +13more
    pdf
    Updated Jul 16, 2025
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    SPREP (2025). Inform E-learning GIS Course [Dataset]. https://americansamoa-data.sprep.org/dataset/inform-e-learning-gis-course
    Explore at:
    pdf(658923), pdf(501586), pdf(1335336), pdf(587295)Available download formats
    Dataset updated
    Jul 16, 2025
    Dataset provided by
    Pacific Regional Environment Programmehttps://www.sprep.org/
    License

    Public Domain Mark 1.0https://creativecommons.org/publicdomain/mark/1.0/
    License information was derived automatically

    Area covered
    Pacific Region
    Description

    This dataset holds all materials for the Inform E-learning GIS course

  2. BOGS Training Metrics

    • catalog.data.gov
    • s.cnmilf.com
    Updated Sep 11, 2025
    + more versions
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Bureau of Indian Affairs (2025). BOGS Training Metrics [Dataset]. https://catalog.data.gov/dataset/bogs-training-metrics
    Explore at:
    Dataset updated
    Sep 11, 2025
    Dataset provided by
    Bureau of Indian Affairshttp://www.bia.gov/
    Description

    Through the Department of the Interior-Bureau of Indian Affairs Enterprise License Agreement (DOI-BIA ELA) program, BIA employees and employees of federally-recognized Tribes may access a variety of geographic information systems (GIS) online courses and instructor-led training events throughout the year at no cost to them. These online GIS courses and instructor-led training events are hosted by the Branch of Geospatial Support (BOGS) or offered by BOGS in partnership with other organizations and federal agencies. Online courses are self-paced and available year-round, while instructor-led training events have limited capacity and require registration and attendance on specific dates. This dataset does not any training where the course was not completed by the participant or where training was cancelled or otherwise not able to be completed. Point locations depict BIA Office locations or Tribal Office Headquarters. For completed trainings where a participant location was not provided a point locations may not be available. For more information on the Branch of Geospatial Support Geospatial training program, please visit:https://www.bia.gov/service/geospatial-training.

  3. m

    GIS course Training Flier

    • maconinsights.maconbibb.us
    Updated Aug 19, 2021
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Macon-Bibb County Government (2021). GIS course Training Flier [Dataset]. https://maconinsights.maconbibb.us/documents/ed385f781f584f48b26bf5d1fd967611
    Explore at:
    Dataset updated
    Aug 19, 2021
    Dataset authored and provided by
    Macon-Bibb County Government
    Area covered
    Description

    This is GIS course announcement flier.

  4. d

    Seattle Parks and Recreation GIS Map Layer Web Services URL - Golf Courses

    • catalog.data.gov
    • cos-data.seattle.gov
    • +1more
    Updated Jan 31, 2025
    + more versions
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    data.seattle.gov (2025). Seattle Parks and Recreation GIS Map Layer Web Services URL - Golf Courses [Dataset]. https://catalog.data.gov/dataset/seattle-parks-and-recreation-gis-map-layer-web-services-url-golf-courses-5cda6
    Explore at:
    Dataset updated
    Jan 31, 2025
    Dataset provided by
    data.seattle.gov
    Area covered
    Seattle
    Description

    Seattle Parks and Recreation ARCGIS park feature map layer web services are hosted on Seattle Public Utilities' ARCGIS server. This web services URL provides a live read only data connection to the Seattle Parks and Recreations Golf Courses dataset.

  5. H

    Golf Courses

    • opendata.hawaii.gov
    • geoportal.hawaii.gov
    • +1more
    Updated Sep 29, 2023
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Office of Planning (2023). Golf Courses [Dataset]. https://opendata.hawaii.gov/dataset/golf-courses
    Explore at:
    geojson, arcgis geoservices rest api, kml, html, ogc wms, ogc wfs, pdf, csv, zipAvailable download formats
    Dataset updated
    Sep 29, 2023
    Dataset provided by
    Hawaii Statewide GIS Program
    Authors
    Office of Planning
    Description
    [Metadata] Locations of golf courses in the State of Hawaii as of August 2023.
    Source: Downloaded by Hawaii Statewide GIS Program staff from Hawaii State Golf Association website (https://hawaiistategolf.org), 8/8/23. NOTE: This data layer shows the status of golf courses BEFORE THE MAUI WILDFIRES OF AUGUST 2023. Geocoded using Esri's World Geocoder. Modified some locations based on satellite imagery, various road layers, etc.

    For more information, please see metadata at https://files.hawaii.gov/dbedt/op/gis/data/golf_courses.pdf or contact Hawaii Statewide GIS Program, Office of Planning and Sustainable Development, State of Hawaii; PO Box 2359, Honolulu, Hi. 96804; (808) 587-2846; email: gis@hawaii.gov; Website: https://planning.hawaii.gov/gis.
  6. Z

    Survey data for "Remote Sensing & GIS Training in Ecology and Conservation"

    • data.niaid.nih.gov
    • zenodo.org
    Updated Jan 24, 2020
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Ulloa-Torrealba, Yrneh Z. (2020). Survey data for "Remote Sensing & GIS Training in Ecology and Conservation" [Dataset]. https://data.niaid.nih.gov/resources?id=zenodo_49870
    Explore at:
    Dataset updated
    Jan 24, 2020
    Dataset provided by
    Wohlfahrt, Christian
    Ortmann, Antonia
    Ulloa-Torrealba, Yrneh Z.
    Bell, Alexandra
    Bernd, Asja
    Braun, Daniela
    License

    CC0 1.0 Universal Public Domain Dedicationhttps://creativecommons.org/publicdomain/zero/1.0/
    License information was derived automatically

    Description

    This file provides the raw data of an online survey intended at gathering information regarding remote sensing (RS) and Geographical Information Systems (GIS) for conservation in academic education. The aim was to unfold best practices as well as gaps in teaching methods of remote sensing/GIS, and to help inform how these may be adapted and improved. A total of 73 people answered the survey, which was distributed through closed mailing lists of universities and conservation groups.

  7. Data from: GIScience

    • ckan.americaview.org
    Updated Sep 10, 2022
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    ckan.americaview.org (2022). GIScience [Dataset]. https://ckan.americaview.org/dataset/giscience
    Explore at:
    Dataset updated
    Sep 10, 2022
    Dataset provided by
    CKANhttps://ckan.org/
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    In this course, you will explore the concepts, principles, and practices of acquiring, storing, analyzing, displaying, and using geospatial data. Additionally, you will investigate the science behind geographic information systems and the techniques and methods GIS scientists and professionals use to answer questions with a spatial component. In the lab section, you will become proficient with the ArcGIS Pro software package. This course will prepare you to take more advanced geospatial science courses. You will be asked to work through a series of modules that present information relating to a specific topic. You will also complete a series of lab exercises, assignments, and less guided challenges. Please see the sequencing document for our suggestions as to the order in which to work through the material. To aid in working through the lecture modules, we have provided PDF versions of the lectures with the slide notes included. This course makes use of the ArcGIS Pro software package from the Environmental Systems Research Institute (ESRI), and directions for installing the software have also been provided. If you are not a West Virginia University student, you can still complete the labs, but you will need to obtain access to the software on your own.

  8. d

    Golf Courses

    • catalog.data.gov
    • data.seattle.gov
    • +2more
    Updated Aug 23, 2025
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    City of Seattle ArcGIS Online (2025). Golf Courses [Dataset]. https://catalog.data.gov/dataset/golf-courses-6a22b
    Explore at:
    Dataset updated
    Aug 23, 2025
    Dataset provided by
    City of Seattle ArcGIS Online
    Description

    Seattle Parks and Recreation Golf Course locations. SPR Golf Courses are managed by contractors.Refresh Cycle: WeeklyFeature Class: DPR.GolfCourse

  9. H

    Digital Elevation Models and GIS in Hydrology (M2)

    • hydroshare.org
    • beta.hydroshare.org
    • +1more
    zip
    Updated Jun 7, 2021
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Irene Garousi-Nejad; Belize Lane (2021). Digital Elevation Models and GIS in Hydrology (M2) [Dataset]. http://doi.org/10.4211/hs.9c4a6e2090924d97955a197fea67fd72
    Explore at:
    zip(88.2 MB)Available download formats
    Dataset updated
    Jun 7, 2021
    Dataset provided by
    HydroShare
    Authors
    Irene Garousi-Nejad; Belize Lane
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Area covered
    Description

    This resource contains data inputs and a Jupyter Notebook that is used to introduce Hydrologic Analysis using Terrain Analysis Using Digital Elevation Models (TauDEM) and Python. TauDEM is a free and open-source set of Digital Elevation Model (DEM) tools developed at Utah State University for the extraction and analysis of hydrologic information from topography. This resource is part of a HydroLearn Physical Hydrology learning module available at https://edx.hydrolearn.org/courses/course-v1:Utah_State_University+CEE6400+2019_Fall/about

    In this activity, the student learns how to (1) derive hydrologically useful information from Digital Elevation Models (DEMs); (2) describe the sequence of steps involved in mapping stream networks, catchments, and watersheds; and (3) compute an approximate water balance for a watershed-based on publicly available data.

    Please note that this exercise is designed for the Logan River watershed, which drains to USGS streamflow gauge 10109000 located just east of Logan, Utah. However, this Jupyter Notebook and the analysis can readily be applied to other locations of interest. If running the terrain analysis for other study sites, you need to prepare a DEM TIF file, an outlet shapefile for the area of interest, and the average annual streamflow and precipitation data. - There are several sources to obtain DEM data. In the U.S., the DEM data (with different spatial resolutions) can be obtained from the National Elevation Dataset available from the national map (http://viewer.nationalmap.gov/viewer/). Another DEM data source is the Shuttle Radar Topography Mission (https://www2.jpl.nasa.gov/srtm/), an international research effort that obtained digital elevation models on a near-global scale (search for Digital Elevation at https://www.usgs.gov/centers/eros/science/usgs-eros-archive-products-overview?qt-science_center_objects=0#qt-science_center_objects). - If not already available, you can generate the outlet shapefile by applying basic terrain analysis steps in geospatial information system models such as ArcGIS or QGIS. - You also need to obtain average annual streamflow and precipitation data for the watershed of interest to assess the annual water balance and calculate the runoff ratio in this exercise. In the U.S., the streamflow data can be obtained from the USGS NWIS website (https://waterdata.usgs.gov/nwis) and the precipitation from PRISM (https://prism.oregonstate.edu/normals/). Note that using other datasets may require preprocessing steps to make data ready to use for this exercise.

  10. Rural & Statewide GIS/Data Needs (HEPGIS) - Federal Aid Functional Class

    • catalog.data.gov
    • data.virginia.gov
    • +1more
    Updated May 8, 2024
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Federal Highway Administration (2024). Rural & Statewide GIS/Data Needs (HEPGIS) - Federal Aid Functional Class [Dataset]. https://catalog.data.gov/dataset/rural-statewide-gis-data-needs-hepgis-federal-aid-functional-class
    Explore at:
    Dataset updated
    May 8, 2024
    Dataset provided by
    Federal Highway Administrationhttps://highways.dot.gov/
    Description

    HEPGIS is a web-based interactive geographic map server that allows users to navigate and view geo-spatial data, print maps, and obtain data on specific features using only a web browser. It includes geo-spatial data used for transportation planning. HEPGIS previously received ARRA funding for development of Economically distressed Area maps. It is also being used to demonstrate emerging trends to address MPO and statewide planning regulations/requirements , enhanced National Highway System, Primary Freight Networks, commodity flows and safety data . HEPGIS has been used to help implement MAP-21 regulations and will help implement the Grow America Act, particularly related to Ladder of Opportunities and MPO reforms.

  11. Climate data and geographic data from Madagascar for learning multi-criteria...

    • zenodo.org
    zip
    Updated Dec 8, 2022
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Francesco Pirotti; Francesco Pirotti (2022). Climate data and geographic data from Madagascar for learning multi-criteria analysis in GIS courses [Dataset]. http://doi.org/10.5281/zenodo.7367873
    Explore at:
    zipAvailable download formats
    Dataset updated
    Dec 8, 2022
    Dataset provided by
    Zenodohttp://zenodo.org/
    Authors
    Francesco Pirotti; Francesco Pirotti
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    Climate data and geographic data from Madagascar for learning multi-criteria analysis in GIS courses.

  12. d

    Golf Courses

    • catalog.data.gov
    • opendata.dc.gov
    • +1more
    Updated Feb 5, 2025
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    D.C. Office of the Chief Technology Officer (2025). Golf Courses [Dataset]. https://catalog.data.gov/dataset/golf-courses-1a3c0
    Explore at:
    Dataset updated
    Feb 5, 2025
    Dataset provided by
    D.C. Office of the Chief Technology Officer
    Description

    The dataset contains locations and attributes of Golf Courses, created as part of the DC Geographic Information System (DC GIS) for the D.C. Office of the Chief Technology Officer (OCTO) and participating D.C. government agencies.

  13. Fieldwork area exploration tutorials (for undergraduate field course)

    • figshare.com
    pdf
    Updated Aug 19, 2016
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Wouter Marra (2016). Fieldwork area exploration tutorials (for undergraduate field course) [Dataset]. http://doi.org/10.6084/m9.figshare.3472940.v2
    Explore at:
    pdfAvailable download formats
    Dataset updated
    Aug 19, 2016
    Dataset provided by
    Figsharehttp://figshare.com/
    Authors
    Wouter Marra
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    Instructions for students to use aerial photos, Google Earth and QGIS to explore their fieldwork area prior to their field trip. This material was designed for first-year undergraduate Earth Sciences students, in preparation to a fieldwork in the French Alps. The fieldwork and this guide focuses on understanding the geology and geomorphology.The accompanying dataset.zip contains required gis-data, which are a DEM (SRTM) and Satellite images (Landsat). This dataset is without a topographic map (SCAN25 from IGN) due to licence constraint. For academic use, request your own licence from IGN (ign.fr) directly.

  14. a

    Golf Courses

    • opendata-mcgov-gis.hub.arcgis.com
    • hub.arcgis.com
    Updated Oct 18, 2023
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Montgomery County, MD (2023). Golf Courses [Dataset]. https://opendata-mcgov-gis.hub.arcgis.com/datasets/golf-courses-1
    Explore at:
    Dataset updated
    Oct 18, 2023
    Dataset authored and provided by
    Montgomery County, MD
    Area covered
    Description

    Updated as needed by TEBS-GIS using various sources.Can be downloaded from the GIS Data Portal here.Access directly in the TEBS-GIS database in SDE.LOCATIONS, SDE.Golf

  15. g

    WWDC GIS Standards - Training Webinar

    • data.geospatialhub.org
    • hub.arcgis.com
    Updated Feb 1, 2018
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    wrds_wdo (2018). WWDC GIS Standards - Training Webinar [Dataset]. https://data.geospatialhub.org/documents/e98e6ddb9f074f9f94256b080a7ee509
    Explore at:
    Dataset updated
    Feb 1, 2018
    Dataset authored and provided by
    wrds_wdo
    Description

    Bear River Data Model GIS Standards Training Webinar (Nov. 15, 2017)

  16. d

    GIS Features of the Geospatial Fabric for National Hydrologic Modeling

    • catalog.data.gov
    • data.usgs.gov
    • +4more
    Updated Sep 17, 2025
    + more versions
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    U.S. Geological Survey (2025). GIS Features of the Geospatial Fabric for National Hydrologic Modeling [Dataset]. https://catalog.data.gov/dataset/gis-features-of-the-geospatial-fabric-for-national-hydrologic-modeling
    Explore at:
    Dataset updated
    Sep 17, 2025
    Dataset provided by
    United States Geological Surveyhttp://www.usgs.gov/
    Description

    The Geopspatial Fabric provides a consistent, documented, and topologically connected set of spatial features that create an abstracted stream/basin network of features useful for hydrologic modeling.The GIS vector features contained in this Geospatial Fabric (GF) data set cover the lower 48 U.S. states, Hawaii, and Puerto Rico. Four GIS feature classes are provided for each Region: 1) the Region outline ("one"), 2) Points of Interest ("POIs"), 3) a routing network ("nsegment"), and 4) Hydrologic Response Units ("nhru"). A graphic showing the boundaries for all Regions is provided at http://dx.doi.org/doi:10.5066/F7542KMD. These Regions are identical to those used to organize the NHDPlus v.1 dataset (US EPA and US Geological Survey, 2005). Although the GF Feature data set has been derived from NHDPlus v.1, it is an entirely new data set that has been designed to generically support regional and national scale applications of hydrologic models. Definition of each type of feature class and its derivation is provided within the

  17. f

    Data from: Self-assessment in student’s learning and developing teaching in...

    • tandf.figshare.com
    txt
    Updated May 29, 2024
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Nora Fagerholm; Eliisa Lotsari; Tua Nylén; Niina Käyhkö; Jussi Nikander; Vesa Arki; Risto Kalliola (2024). Self-assessment in student’s learning and developing teaching in geoinformatics – case of Geoportti self-assessment tool [Dataset]. http://doi.org/10.6084/m9.figshare.24099390.v1
    Explore at:
    txtAvailable download formats
    Dataset updated
    May 29, 2024
    Dataset provided by
    Taylor & Francis
    Authors
    Nora Fagerholm; Eliisa Lotsari; Tua Nylén; Niina Käyhkö; Jussi Nikander; Vesa Arki; Risto Kalliola
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    In successful geoinformatics education, students’ active role in the learning process, e.g. through applying self-assessment, show an increasing interest but the evidence of benefits and challenges of self-assessment are sporadic. In this article, we examine the usefulness of an online self-assessment tool developed for geoinformatics education. We gathered data in two Finnish universities on five courses (n = 11–73 students/course) between 2019 and 2021. We examined 1) how the students’ self-assessed knowledge and understanding in geoinformatics subject topics changed during a course, 2) how the competencies at the end of a course changed between the years in different courses, and 3) what was the perceived usefulness of the self-assessment approach among the students. The results indicate support for the implementation of self-assessment, both as a formative and summative assessment. However, it is crucial to ensure that the students understand the contents of the self-assessment subject topics. To increase students’ motivation to take a self-assessment, it is crucial that the teacher actively highlights how it supports their studying and learning. As the teachers of the examined courses, we discuss the benefits and challenges of the self-assessment approach and the applied tool for the future development of geoinformatics education.

  18. n

    LANDISVIEW 2.0 : Free Spatial Data Analysis

    • cmr.earthdata.nasa.gov
    Updated Mar 5, 2021
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    (2021). LANDISVIEW 2.0 : Free Spatial Data Analysis [Dataset]. https://cmr.earthdata.nasa.gov/search/concepts/C1214586381-SCIOPS
    Explore at:
    Dataset updated
    Mar 5, 2021
    Time period covered
    Jan 1, 1970 - Present
    Description

    LANDISVIEW is a tool, developed at the Knowledge Engineering Laboratory at Texas A&M University, to visualize and animate 8-bit/16-bit ERDAS GIS format (e.g., LANDIS and LANDIS-II output maps). It can also convert 8-bit/16-bit ERDAS GIS format into ASCII and batch files. LANDISVIEW provides two major functions: 1) File Viewer: Files can be viewed sequentially and an output can be generated as a movie file or as an image file. 2) File converter: It will convert the loaded files for compatibility with 3rd party software, such as Fragstats, a widely used spatial analysis tool. Some available features of LANDISVIEW include: 1) Display cell coordinates and values. 2) Apply user-defined color palette to visualize files. 3) Save maps as pictures and animations as video files (*.avi). 4) Convert ERDAS files into ASCII grids for compatibility with Fragstats. (Source: http://kelab.tamu.edu/)

  19. G

    Geographic Information System (GIS) Software Market Research Report 2033

    • growthmarketreports.com
    csv, pdf, pptx
    Updated Sep 1, 2025
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Growth Market Reports (2025). Geographic Information System (GIS) Software Market Research Report 2033 [Dataset]. https://growthmarketreports.com/report/geographic-information-system-software-market-global-industry-analysis
    Explore at:
    csv, pptx, pdfAvailable download formats
    Dataset updated
    Sep 1, 2025
    Dataset authored and provided by
    Growth Market Reports
    Time period covered
    2024 - 2032
    Area covered
    Global
    Description

    Geographic Information System (GIS) Software Market Outlook



    According to our latest research, the global Geographic Information System (GIS) Software market size reached USD 11.6 billion in 2024, reflecting a robust demand for spatial data analytics and location-based services across various industries. The market is experiencing a significant growth trajectory, driven by a CAGR of 12.4% from 2025 to 2033. By the end of 2033, the GIS Software market is forecasted to attain a value of USD 33.5 billion. This remarkable expansion is primarily attributed to the integration of advanced technologies such as artificial intelligence, IoT, and cloud computing, which are enhancing the capabilities and accessibility of GIS platforms.




    One of the major growth factors propelling the GIS Software market is the increasing adoption of location-based services across urban planning, transportation, and utilities management. Governments and private organizations are leveraging GIS solutions to optimize infrastructure development, streamline resource allocation, and improve emergency response times. The proliferation of smart city initiatives worldwide has further fueled the demand for GIS tools, as urban planners and municipal authorities require accurate spatial data for effective decision-making. Additionally, the evolution of 3D GIS and real-time mapping technologies is enabling more sophisticated modeling and simulation, expanding the scope of GIS applications beyond traditional mapping to include predictive analytics and scenario planning.




    Another significant driver for the GIS Software market is the rapid digitization of industries such as agriculture, mining, and oil & gas. Precision agriculture, for example, relies heavily on GIS platforms to monitor crop health, manage irrigation, and enhance yield forecasting. Similarly, the mining sector uses GIS for exploration, environmental impact assessment, and asset management. The integration of remote sensing data with GIS software is providing stakeholders with actionable insights, leading to higher efficiency and reduced operational risks. Furthermore, the growing emphasis on environmental sustainability and regulatory compliance is prompting organizations to invest in advanced GIS solutions for monitoring land use, tracking deforestation, and managing natural resources.



    The evolution of 3D GIS is revolutionizing the way spatial data is visualized and analyzed, offering a more immersive and detailed perspective of geographic information. This technology allows for the creation of three-dimensional models that provide a realistic representation of urban landscapes, infrastructure, and natural environments. By integrating 3D GIS with real-time data feeds, organizations can enhance their spatial analysis capabilities, enabling more accurate simulations and predictions. This advancement is particularly beneficial for urban planners and architects who require detailed visualizations to assess the impact of new developments and infrastructure projects. Moreover, 3D GIS is facilitating better communication and collaboration among stakeholders by providing a common platform for visualizing complex spatial data.




    The expanding use of cloud-based GIS solutions is also a key factor driving market growth. Cloud deployment offers scalability, cost-effectiveness, and remote accessibility, making GIS tools more accessible to small and medium enterprises as well as large organizations. The cloud model supports real-time data sharing and collaboration, which is particularly valuable for disaster management and emergency response teams. As organizations increasingly prioritize digital transformation, the demand for cloud-native GIS platforms is expected to rise, supported by advancements in data security, interoperability, and integration with other enterprise systems.




    Regionally, North America remains the largest market for GIS Software, accounting for a significant share of global revenues. This leadership is underpinned by substantial investments in smart infrastructure, advanced transportation systems, and environmental monitoring programs. The Asia Pacific region, however, is witnessing the fastest growth, driven by rapid urbanization, government-led digital initiatives, and the expansion of the utility and agriculture sectors. Europe continues to demonstrate steady adoption, particularly in environmental manage

  20. Esri Maps for Public Policy

    • climate-center-lincolninstitute.hub.arcgis.com
    • ilcn-lincolninstitute.hub.arcgis.com
    • +4more
    Updated Oct 1, 2019
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Esri (2019). Esri Maps for Public Policy [Dataset]. https://climate-center-lincolninstitute.hub.arcgis.com/datasets/esri::esri-maps-for-public-policy
    Explore at:
    Dataset updated
    Oct 1, 2019
    Dataset authored and provided by
    Esrihttp://esri.com/
    Description

    OVERVIEWThis site is dedicated to raising the level of spatial and data literacy used in public policy. We invite you to explore curated content, training, best practices, and datasets that can provide a baseline for your research, analysis, and policy recommendations. Learn about emerging policy questions and how GIS can be used to help come up with solutions to those questions.EXPLOREGo to your area of interest and explore hundreds of maps about various topics such as social equity, economic opportunity, public safety, and more. Browse and view the maps, or collect them and share via a simple URL. Sharing a collection of maps is an easy way to use maps as a tool for understanding. Help policymakers and stakeholders use data as a driving factor for policy decisions in your area.ISSUESBrowse different categories to find data layers, maps, and tools. Use this set of content as a driving force for your GIS workflows related to policy. RESOURCESTo maximize your experience with the Policy Maps, we’ve assembled education, training, best practices, and industry perspectives that help raise your data literacy, provide you with models, and connect you with the work of your peers.

Share
FacebookFacebook
TwitterTwitter
Email
Click to copy link
Link copied
Close
Cite
SPREP (2025). Inform E-learning GIS Course [Dataset]. https://americansamoa-data.sprep.org/dataset/inform-e-learning-gis-course
Organization logo

Inform E-learning GIS Course

Explore at:
pdf(658923), pdf(501586), pdf(1335336), pdf(587295)Available download formats
Dataset updated
Jul 16, 2025
Dataset provided by
Pacific Regional Environment Programmehttps://www.sprep.org/
License

Public Domain Mark 1.0https://creativecommons.org/publicdomain/mark/1.0/
License information was derived automatically

Area covered
Pacific Region
Description

This dataset holds all materials for the Inform E-learning GIS course

Search
Clear search
Close search
Google apps
Main menu